This is a guest post for the Computer Weekly Developer Network written by Bob De Caux, director of AI and RPA at IFS.
IFS is known for its industrial cloud software deployments with a specific focus in areas including Field Service Management (FSM), Enterprise Asset Management (EAM) and Enterprise Resource Planning (ERP) systems.
TechTarget defines Robotic Process Automation (RPA) is the use of software with Artificial Intelligence and Machine Learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform — these tasks can include queries, calculations and maintenance of records and transactions.
De Caux writes as follows…
The fastest-growing segment of the global enterprise software market, Robotic Process Automation (RPA) has proven itself to be a highly effective tool for transforming and streamlining the way organisations operate. But in the hype surrounding the technology, we shouldn’t over-estimate its capabilities.
In our own experience as a software company, we’ve found that RPA works well for our customers as a quick and easy way to integrate our software with other systems, especially in terms of replicating the GUI steps that users go through when moving data into or out of our software.
However, RPA providers have realised that going ‘end-to-end’ on a business process across multiple applications is very difficult. Despite clever advances that use AI-driven image recognition to improve flexibility, replicating the actions a user takes through a GUI is not robust to changes in the underlying software in the same way that interacting through an Application Programming Interface (API) would be.
Therefore, RPA will increasingly become about orchestration, maintaining simplicity by encapsulating defined API-driven interactions with software that perform clearly defined tasks as pieces that can be easily added dragged and dropped into RPA workflows.
The onus now will be on software companies (such as us) to create APIs that are easily consumable by RPA software, but it also creates an opportunity to provide more advanced process automation logic deeper within our products, which can take advantage of usage data and AI in a way that external RPA engines can never access. Through this approach, external RPA engines and internal process automation engines will start to work together more efficiently.
RPA combos are key
The evolution of RPA, therefore, hinges on how it’s utilised alongside other technologies.
RPA forms a key part of ‘intelligent automation’ along with Business Process Automation (BPA) and AI. Speaking from personal experience, we drive intelligent automation within our own software using a combination of effective BPA and machine learning to optimise process effectiveness, which while not traditionally thought of as RPA, has proven to be a highly effective method of automation.
As RPA adoption increases, we expect to see machine learning increasingly used on RPA-driven workflows to optimise processes across multiple systems.
When looking to RPA, businesses must look beyond just short-term efficiency gains and understand its potential as part of the broader technology ecosystem.
In doing this, they will be best placed to harness its full benefits, and go up, up and RPAway!